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522 organizations since 2016

Filter by stack, capacity and track record. Every number comes from Google's public archive.

Since 2016 522GSoC 2026 183
AllEvery cycle since 201640First time in 202617Ten or more contributors27Growing in 202613Back after a break22

Showing 1–24 of 36 organizations

PythonJavaGitPython 3JavaScriptPythonData scienceClear all

  • CloudCV

    Web

    Building platforms for reproducible AI Research

    2026
    –
    Cycles
    9
    Projects
    28
    Trend
    PythonJavaScriptLuaCaffe+13

  • DBpedia

    Data

    DBpedia is a crowd-sourced community effort to extract structured information from Wikipedia and make this information available on the Web. It allows for a global and unified access to Knowledge Graphs.

    2026
    5
    Cycles
    11
    Projects
    66
    Trend
    PythonJavaScalaRDF+6

  • Django Software Foundation

    Web

    Django is a high-level Python Web framework originally developed at the Lawrence-Journal World. Django was designed to handle two challenges: the intensive deadlines of a newsroom and the stringent requirements of the experienced Web developers who wrote it. It lets you build high-performing, elegant Web applications quickly.

    2026
    4
    Cycles
    11
    Projects
    23
    Trend
    PythonDjango

  • Genome Assembly and Annotation

    Science and medicine

    EMBL-EBI is a global centre for biological data, developing and maintaining open data resources and open-source software that support life science research worldwide. Our services are used daily by researchers across academia, healthcare, and industry, and span genomics, transcriptomics, metagenomics, molecular interactions, chemistry, and functional annotation.

    2026
    7
    Cycles
    4
    Projects
    21
    Trend
    PythonMySQLJavaScriptRust+3

  • GeomScale

    Science and medicine

    GeomScale is a research and development project that delivers open source code for state-of-the-art algorithms for problems at the intersection of data science, optimization, geometric, and statistical computing. The current focus of GeomScale is on scalable algorithms for sampling from high-dimensional distributions, integration, convex optimization, and their applications. One of our ambitions is to fill the gap between theory and practice by turning state-of-the-art theoretical tools in geometry and optimization to state-of-the-art implementations. Towards this goal, we will deliver various innovative solutions in a variety of application fields, like finance, computational biology, and statistics that will extend the limits of contemporary computational tools. GeomScale aims in serving as a building block for an international, interdisciplinary, and open community in high dimensional geometrical and statistical computing. The main development is currently performed in volesti, a generic open source C++ library, with R and python interfaces (the latter is hosted in package dingo), for high-dimensional sampling, volume approximation, and copula estimation for financial modelling. In particular, the current implementation scales up to hundred or thousand dimensions, depending on the problem. To our knowledge it is the most efficient software package for sampling and volume computation to date. It is, in several cases, orders of magnitude faster compared to packages that solve the same problems. It can be used to compute challenging multivariate integrals and to approximate optimal solutions in optimization problems. It has already found important applications in systems biology by analyzing large metabolic networks (e.g., the latest human network) and in FinTech by detecting shock events and by evaluating portfolios performance in stock markets with thousands of assets. Other application areas include AI and in particular approximate weighted model integration. Recent studies has shown a potential application of volesti methods in trustworthy AI, static analysis of programs and differential privacy.

    2026
    4
    Cycles
    7
    Projects
    34
    Trend
    PythonC++RJupyter+1

  • Google DeepMind

    Artificial Intelligence

    Google DeepMind's open-source projects

    2026
    –
    Cycles
    1
    Projects
    45
    Trend
    PythonJavaScriptTypeScriptJAX+1

  • INCF

    Science and medicine

    The International Neuroinformatics Coordinating Facility (INCF; www.incf.org) is an international organization launched in 2005, following a proposal from the Global Science Forum of the OECD.

    2026
    23
    Cycles
    11
    Projects
    234
    Trend
    PythonJavaScriptJavaC+++6

  • InterMine

    Science and medicine

    Integrating biological data sources, making it easy to query and analyse data

    2026
    –
    Cycles
    2
    Projects
    12
    Trend
    PythonPostgreSQLJavaScriptJava+2

  • IOOS

    Science and medicine

    U.S. IOOS is a national and regional partnership working to provide ocean, coastal and Great Lakes observations, data, tools, and forecasts to improve safety, enhance the economy, and protect our environment. Our primary purpose is to provide free and open data about the state of our oceans and Great Lakes to our users. These data are fundamental to understanding the health of our marine ecosystems, to monitor the climate signal as captured in oceanographic conditions, and to provide predictions about the future state of our oceans and coasts.

    2026
    7
    Cycles
    5
    Projects
    29
    Trend
    PythonBig Data ScienceOcean TechnologyOcean Science+4

  • KNIME

    Data

    Open for Innovation

    2026
    –
    Cycles
    1
    Projects
    2
    Trend
    JavaScriptJavaTensorFlow

  • Metaflow

    Infrastructure and cloudNew in 2026

    Metaflow is a human-friendly Python library that makes it straightforward to develop, deploy, and operate various kinds of data-intensive applications, in particular those involving data science, ML, and AI. Metaflow was originally developed at Netflix to boost the productivity of data scientists who work on a wide variety of projects, from classical statistics to state-of-the-art deep learning.

    2026
    2
    Cycles
    1
    Projects
    2
    Trend
    PythonJavaScriptKubernetes

  • mlpack

    Science and medicine

    a fast, flexible machine learning library

    2026
    –
    Cycles
    9
    Projects
    60
    Trend
    C++PythonMachine learningDeep Learning+3

  • MZmine and MS-DIAL

    Science and medicine

    Open-source software for mass spectrometry

    2026
    –
    Cycles
    1
    Projects
    2
    Trend
    JavaC#JavaFX

  • National Resource for Network Biology (NRNB)

    Science and medicine

    The National Resource for Network Biology (NRNB, https://nrnb.org) organizes the development of free, open-source software technologies to enable network-based visualization, analysis, and biomedical discovery. Biomedical research is increasingly dependent on knowledge expressed in terms of networks, including gene, protein and drug interactions, cell-cell and viral-host communication, and vast social networks. Our technologies enable researchers to assemble and analyze these networks and to use them to better understand biological systems and, in particular, how they fail in disease. The NRNB mentoring organization includes projects such as Cytoscape (https://cytoscape.org/), WikiPathways (https://wikipathways.org/), SBML (https://sbml.org/), SBGN (https://sbgn.github.io/) and others. This is a great opportunity to work at the intersection of biology and computing! For example, Cytoscape is downloaded over 24,000 times per month by researchers. We take mentoring seriously and are proud of our 96% success rate (https://nrnb.org/alumni.html#gsoc-tab) with former students and projects. But don’t take our word for it, read testimonials from prior NRNB students (https://nrnb.org/testimonials.html#student-tab) and mentors (https://nrnb.org/testimonials.html#mentor-tab). Find out more about the software projects being developed in coordination with NRNB at our website (https://nrnb.org). Also refer to our GSoC page (https://nrnb.org/gsoc.html) for additional resources and application tips.

    2026
    7
    Cycles
    11
    Projects
    126
    Trend
    PythonJavaScriptJavaC+++10

  • NumFOCUS

    Science and medicine

    NumFOCUS supports and promotes world-class, innovative, open source scientific software. Most individual projects, even the wildly successful ones, find the overhead of a non-profit to be too large for their community to bear. NumFOCUS provides a critical service as an umbrella organization for this projects.

    2026
    27
    Cycles
    11
    Projects
    304
    Trend
    PythonJavaScriptRJulia+2

  • Open Chemistry

    Science and medicine

    Advancing Open Source & Open Science for Chemistry

    2026
    –
    Cycles
    9
    Projects
    51
    Trend
    PythonJavaScriptOpenGLC+++6

  • Open Chromosome Collective

    Science and medicine

    Open-Source Tools for 3D Genomics Research

    2026
    –
    Cycles
    1
    Projects
    3
    Trend
    PythonNumPyscikit-learnpandas+1

  • Open Technologies Alliance - GFOSS

    Science and medicine

    Open Technologies Alliance (GFOSS) is a non-profit organization, with 37 Universities and Research Centers as its shareholders. Our main goal is to promote Openness. GFOSS – Open Technologies Alliance is a platform for Open Standards, Free Software, Open Content, Open Data & Open Hardware in Greece. The major Greek Universities and Research Centers participate in GFOSS – Open Technologies Alliance, while leading members of the Greek community of developers play a key role in the implementation of our policies. Through our initiatives we aspire to contribute and coordinate the efforts of groups of volunteers, public servants, university researchers and students enabling them to form the backbone of Greek FOSS development and implementation. GFOSS is one of the strategic actors for the promotion of OSS throughout Greece (see https://joinup.ec.europa.eu/sites/default/files/inline-files/OSS%20Country%20Intelligence%20Report_GR.pdf ). Many public administrations and academic institutions collaborate with GFOSS to implement open source projects and through Google Summer of Code we give the opportunity to students to actively engage in the production and the actual implementation of an open source project. GFOSS also contributes and advises on the development of various open source projects related to e-government and digital transformation in Greece (e.g. https://howto.gov.gr/ - https://forma.gov.gr/) and actively promotes the use of Open Source software and hardware in the Greek primary and secondary education through the Open Educational Technologies Competition (https://openedtech.ellak.gr/ )

    2026
    7
    Cycles
    9
    Projects
    77
    Trend
    PythonMySQLJavaPHP+16

  • OpenAstronomy

    Science and medicine

    OpenAstronomy is a collaboration between open source astronomy, astrophysics & heliophysics projects that are used by researchers and software engineers around the world to study our universe either by analysing the data obtained from amazing instruments like the [James Webb Space telescope](https://jwst.nasa.gov/), the [Square Kilometer Array](https://www.skatelescope.org/) or the [Solar Dynamic Observatory](http://sdo.gsfc.nasa.gov/), developing very sophisticated numerical models (eg., [FLASH](http://flash.uchicago.edu/)) or designing interplanetary trajectories for human-made spacecraft. The analysis of such data helps multiple types of research, from being able to forecast solar storms to detecting planets in other stars, to understanding how galaxies are formed to explain the expansion and the origin of the universe.

    2026
    5
    Cycles
    11
    Projects
    82
    Trend
    CPythonJuliaNumPy+6

  • PEcAn Project

    Science and medicine

    Climate change science has witnessed an explosion in the amount and types of data that can be brought to bear on the potential responses of the terrestrial carbon cycle and biodiversity to global change. Many of the most pressing questions about global change are not necessarily limited by the need to collect new data as much as by our ability to synthesize existing data. This project specifically seeks to improve this ability. Because no one measurement provides a complete picture, multiple data sources must be integrated in a sensible manner. Process-based models represent an ideal framework for integrating these data streams because they represent multiple processes at different spatial and temporal scales in ways that capture our current understanding of the causal connections across scales and among data types. Three components are required to bridge this gap between the available data and the required level of understanding: 1) state-of-the-art ecosystem model, 2) a workflow management system to handle the numerous streams of data, and 3) a data assimilation statistical framework in order to synthesize the data with the model.

    2026
    4
    Cycles
    10
    Projects
    34
    Trend
    CPostgreSQLJavaScriptR+7

Contributor counts are accepted projects per cycle.

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